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Jeff Clune
@jeffclune
Associate Professor, CS, U. British Columbia. Faculty Member, Vector Inst. ML, AI, deep RL, deep learning, AI-Generating Algorithms (AIGAs) More: JeffClune.com
San Francisco, CAjeffclune.comJoined July 2010

Jeff Clune’s posts

I am extremely excited to announce (1) I've joined OpenAI to lead a large-scale effort into AI-generating Algorithms research, & (2) I'll be an Associate CS Professor at U. British Columbia in 2021, where I will continue to lead the OpenAI project. Both are dreams come true! 1/2
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Excited to announce I have joined DeepMind as a Senior Research Advisor! I will be working with many fantastic people there on AI-generating algorithms & open-ended learning, one of many areas where @DeepMind is a leader. My roles at UBC & the Vector Institute will stay the same.
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Introducing Video PreTraining (VPT): it learns complex behaviors by watching (pretraining on) vast amounts of online videos. On Minecraft, it produces the first AI capable of crafting diamond tools, which takes humans over 20 minutes (24,000 actions) 🧵👇openai.com/blog/vpt
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Today is my last day at Uber. It's been a dream to have our startup acquired by Uber &, with wonderful colleagues, create Uber AI Labs. I'm proud of our work, eg. Go-Explore, POET, AI-GAs, GTNs, ANML, Differentiable Plasticity, Backpropamine, Deep Neuroevolution, PPGNs, etc. 1/3
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We're hiring software engineers, research engineers, & research scientists on the multi-agent team ! Interested in AI-generating algorithms, many interacting agents, open-ended algorithms, automatically generating training environments, deep RL etc? openai.com/jobs/
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Reviewers in my experience almost always insist on SOTA for publication. This is the result. In doing so, we are asking to be lied to via p-hacking and brittle, non-reproducible results. We also choke off promising directions that are not immediately better, which is ridiculous!
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Reviewing NeuRIPS papers one thing is clear: most of us think, our work needs to be better than others to get published and we sell(modify+highlight+hide) it to convince the reader, putting science second to it.
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I am recruiting PhD students at UBC. I especially encourage applications from those underrepresented in our field. Interested in AI-GAs, meta-learning, generating learning challenges, deep RL, open-endedness, QD, exploration, generalization, continual learning, etc? Please apply!
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I agree. "I'm amazed that people confidently pronounce these things are not sentient, and when you ask them what they mean by sentient they say well they don't really know. So how can you be confident they're not sentient if you don't know what sentient means? "-Geoff Hinton 1/2
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No privacy concerns here. Nope. None at all.
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🤯 Full body tracking now possible using only WiFi signals A deep neural network maps the phase and amplitude of WiFi signals to UV coordinates within 24 human regions The model can estimate the dense pose of multiple subjects by utilizing WiFi signals as the only input 🧵
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AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence arxiv.org/abs/1905.10985 Historically, hand-designed pipelines are ultimately outperformed by entirely learned ones. Will that will be true of creating general AI itself? 1/6
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I think biological development is the most impressive technology in the known universe. Can you think of anything more impressive? A seed (or egg) uses nanotech to gather all the resources needed to self-assemble molecules into a jaguar, hawk, oak tree, whale or human. Amazing!
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A human body is so wonderfully nested. Its ~40T cells descend from individual eukaryotic cells before multi-cellularity. And each has ~1000 mitochondria, which were free-living bacteria before endosymbiosis. And all of it is home to 1-3X as many bacteria in the nooks and crannies
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Go-Explore now solves all unsolved Atari games*, handles stochastic training throughout via goal-conditioned polices, reuses skills to intelligently explore after returning, and solves hard-exploration simulated robotics tasks! New paper led by & 1/6
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Generating multi-modal robot behavior (neural networks that perform many different tasks well) via the new Combinatorial Multi-Objective Evolutionary Algorithm (CMOEA). Very proud of this work. Led by Joost Huizinga Key idea: the more stepping stones the better!
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Delighted to announce my lab was awarded a substantial grant from Open Philanthropy for work on AI alignment, safety, & existential risk. I want to make the development of powerful AI & AGI go as well as possible for humanity, & will allocate more time to these key topics
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Yann LeCun et al. publishing evolutionary algorithm tools. Welcoming the era of deep neuroevolution indeed! (eng.uber.com/deep-neuroevol) Great to see the traditional ML community adopt these tools in the cases when they are useful.
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This library from @ylecun’s lab implemented benchmarked versions of evolutionary computation algorithms such as: Differential Evolution, Fast Genetic Algorithm, CMA-ES, Particle Swarm Optimization. 🦎🐞🐜 twitter.com/ylecun/status/…
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Our paper was accepted at ICLR. Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity. Very exciting work led by , a pioneer in this area. With Aditya Rawal, , and myself
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Join us! Our team at OpenAI is now hiring research scientists and engineers. Interested in AI-generating algorithms, multiple interacting agents, open-ended algorithms, automatically generating training environments, deep RL, and more? Please apply! openai.com/jobs
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Agreed. I remember when I told journalists in 2016 AI would be able to generate any image you (or bad actors) want from a text description and they thought I was nuts. I also predicted videos and entire virtual worlds would come later, which they will! Strap in, society.
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AI Images: Last Week Tonight with John Oliver Text-to-Image has really gone mainstream! Source: youtu.be/3YNku5FKWjw
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I greatly enjoyed giving a guest lecture in 's meta-learning class at Stanford. Thanks to Chelsea for the invitation & for making all of the lectures available for everyone! Mine is a deep dive into AI-GAs, GTNs, differentiable plasticity/backpropamine, ANML, & POET.
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Want to learn about meta-learning? Lecture videos for CS330 are now online! youtube.com/playlist?list= Topics incl. MTL, few-shot learning, Bayesian meta-learning, lifelong learning, meta-RL & more: cs330.stanford.edu + 3 guest lectures from Kate Rakelly, @svlevine, @jeffclune
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Deep Curiosity Search introduces a new type of intrinsic motivation for deep RL: intralife exploration. Just rewarding agents to 'go somewhere new' can dramatically increase performance, tying state of the art on Montezuma’s Revenge arxiv.org/abs/1806.00553 Congrats Chris Stanton!
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Update: Go-Explore remains state of the art on Montezuma’s & Pitfall when *tested* with sticky actions. Should we *require* stochastic training? Depends on the research objectives. Please read newly added section eng.uber.com/go-explore A healthy debate created by Go-Explore.
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VPT was accepted at NeurIPS! Congrats to the team for all the hard work, and a huge thanks to the reviewers and organizers! #NeurIPS2022
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Introducing Video PreTraining (VPT): it learns complex behaviors by watching (pretraining on) vast amounts of online videos. On Minecraft, it produces the first AI capable of crafting diamond tools, which takes humans over 20 minutes (24,000 actions) 🧵👇openai.com/blog/vpt
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I often have ideas for startups, research papers, short stories, etc. I am going to start posting them here to share them, see what people think, and in the hopes of maybe inspiring someone to something related (or even implement the idea). I'll tag things with #someBodyDoThis
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I will be hiring at both institutions, so please watch this space for details on those opportunities if interested. A huge thanks to everyone at both OpenAI and UBC for these wonderful opportunities! I could not be more excited about both! 2/2
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I often have (what I think are) great ideas for startups (especially AI startups). Has someone created a way to suggest ideas to would-be entrepreneurs and then get a small bit of equity if they work on your idea? If not, is that itself a good idea (a site that does that)?
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How can I get rid of all the AI clickbait in my feed? It's mostly from blue checkmark folks. Is there a way to ban/ignore/filter anyone who has one? Are the rest of you inundated with annoying click-baity AI Tweets?
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Another great example of AI outsmarting us. Here scientists took a robot that could solve tasks by picking up a box and then disabled its gripper to see if it could adapt to push the box around. It instead figured out how to pick the box up anyway! arxiv.org/abs/1803.03453
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We are beginning to see how powerful AI can catalyze science. In a future coming to you soon: ask the computer to conduct an experiment, interactively probe the results, and then ask for the next experiment, iterating quickly without writing a single line of code or pipetting!
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GPT-3 Does The Work™️ on generating SVG charts, with a quick web app I built with @billyjeanbillyj. With a short sentence describing what you want to plot, its able to generate charts with titles, labels and legends from about a dozen primed examples. cc @gdb
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Introducing a new algorithm that automatically, intelligently adjusts exploration vs. exploitation for #DeepRL. NSRA-ES exploits until stuck, then increasingly explores. It's newly added to 'Improving Exploration in ES' Great work on it Vashisht Madhavan!
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What is starting to happen to me during quarantine because of no haircuts.
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This sheep escaped a farm and spent 6 years in the mountains, during which time he grew 60 pounds of wool. Wolves tried to eat him, but their teeth could not penetrate the floof. You don't have to turn hard to survive the wolves, just be really, really soft and fluffy.
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Great article about AI-generating Algorithms ("getting AI to make itself"), including POET, GTNs, & ANML Also includes work & quotes from (POET), Esteban Real (AutoML), & (LRL), plus great work by Thanks for the fun interview & article !
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Artificial intelligence might not need us to become smarter than we are. This thread is about how AI is learning how to create itself. technologyreview.com/2021/05/27/102
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Very interesting new work on open-endedness and AI-Generating Algorithms from et al. @DeepMind, with special emphasis on Pillar 3 (automatically generating environments, like in POET). Congrats. I look forward to reading it in detail!
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Very excited to release our new work: Open-Ended Learning Leads to Generally Capable Agents. tldr; algorithm that dynamically shapes task distributions to train agents on huge task space, resulting in surprisingly general behaviour dpmd.ai/open-ended-blog Thread: (1/n)
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A friend of mine has cancer. I generated AI images of her as a superhero fighting cancer and she loved them. She asked if I could produce a 3D-printed version. Anyone know a talented 3D-blender-type artist that also knows how to 3D print their creations that I could hire?
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Being an AI researcher as adult means reliving the video game part of my childhood in order. First Atari, then Super Mario, now streetfighter. Looking forward to Goldeneye next!
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The MAME RL Algorithm Training Toolkit: A Python library that can provide a Gym-like API around almost any old arcade game. They show how to set up new ROMS, and provide RL example for “Street Fighter III Third Strike: Fight for the Future (Japan version)” github.com/M-J-Murray/MAM
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Excited to give a talk at Stanford today to 's meta-learning and multi-task learning class (& open to all at Stanford). Thanks Chelsea for the invitation."How Meta-Learning Could Help Us Accomplish Our Grandest AI Ambitions, and Early, Exotic Steps in that Direction"
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I wish arXiv put affiliations on the html page for a paper. Often that's the only reason I download the PDF, as I am curious where the work came from. I wonder how much bandwidth they'd save by doing that.
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Cool to see our evolved virtual creatures highlighted in Nature Machine Intelligence! Thanks to for the kind words in the article. Work with Nick Cheney, Rob MacCurdy, and Hod Lipson.
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Tired of training #NeuralNetworks? Try optimizing virtual creatures instead. @nature Machine Intelligence article by Sam Kriegman (@Kriegmerica). rdcu.be/bTN0S
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To be fair, I'm moving either way. But how often do you get to say this and really mean it? ;-)
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I am extremely excited to announce (1) I've joined OpenAI to lead a large-scale effort into AI-generating Algorithms research, & (2) I'll be an Associate CS Professor at U. British Columbia in 2021, where I will continue to lead the OpenAI project. Both are dreams come true! 1/2
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Seeking a postdoc to join my lab at UBC! Interested in combining deep RL & large language models to advance open-endedness? Candidates should have pubs in one of: RL, large models, open-endedness, or related areas. 1-2+-year positions in paradise! Apply: jeffclune.com/join.html
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I am delighted to announce that I have been appointed as Canada CIFAR AI Chair. Thanks to everyone at CIFAR and the Vector Institute. Congrats to the other appointees, including
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Happy to announce the appointments of two new Canada CIFAR AI Chairs from UBC Computer Science: Dr. Jeff Clune and Dr. Vered Shwartz Read about their research: ow.ly/7oCb50Ln3YF @jeffclune @VeredShwartz @CIFAR_News @VectorInst #AI #NLP #UBC #CIFAR
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Why leave? I love Uber AI Labs and it has been a dream opportunity, but another opportunity was offered to me that was too amazing to pass up. It also works better for my family. I will announce my future plans Monday, but for today I just wanted to thank my friends at Uber. 3/3
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My MIT talk is online. Thanks to Josh Tenenbaum for the nice introduction. "Improving Deep RL via Quality Diversity, Open-Ended, and AI-Generating Algorithms" (also covers VPT and how that fits into the AI-GA paradigm). Thanks for organizing!
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In line with AI-Generating Algorithms, we should stop trying to hand-design the solutions to ML problems. Instead, with the right problems and enough data/compute, ML will do the heavy lifting and solve the problems for us (and do a better job). arxiv.org/abs/1905.10985
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People have spent a lot of time trying to encode better inductive biases into vision models. This work suggests that such effort may be misdirected. An off-the-shelf Transformer pretrained on a large unlabeled dataset can do just as well at classifying CIFAR-10 as the best CNNs. twitter.com/OpenAI/status/…
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I am delighted that Ken Stanley is joining us at and that we thus will be able to continue to work together so closely!!! Welcome Ken!
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I'm thrilled to announce that I will be joining the superb team at @OpenAI in June, where I will be starting a group (and indeed hiring) focused on achieving open-endedness in machine learning. Looking forward to exploring a novel path!
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